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Über dieses Buch

This book includes a collection of research articles presented at the “6th International Workshop on Hydro Scheduling in Competitive Electricity Markets”. The workshop was a unique and intimate forum for researchers and practitioners to present state-of-the-art research and development concerning novel methodological findings, best practices and real-life applications of hydro scheduling. It also provided a platform for discussing the developments that are taking place in the industry, sharing different experiences and discussing future trends related to this area.

This proceedings book is a collection of the most relevant, high-quality articles from the workshop. Discussing the state-of-the-art in the field of hydro scheduling, it is a valuable resource for a wide audience of researchers and practitioners in the field now and in the interesting and challenging times ahead.

Inhaltsverzeichnis

Frontmatter

Blackbox Optimization for Chance Constrained Hydro Scheduling Problems

This paper presents a novel method to treat a chance constrained formulation of the hydropower reservoir management problem. An advantage of this methodology is that it is easily understandable by the decision makers. However, when using explicit optimization methods, the optimal operating policy requires to be simulated over multiple scenarios to validate the feasibility of the constraints. A blackbox optimization framework is used to determine the parameters of the chance constraints, embedding the chance constrained optimization problem and the simulation as the blackbox. Numerical results are conducted on the Kemano hydropower system in Canada.
Sara Séguin, Pascal Côté

Evaluating Approaches for Estimating the Water Value of a Hydropower Plant in the Day-Ahead Electricity Market

This paper addresses the question of whether the use of complex algorithms, based on mixed integer linear programming, to solve the intrastage decision problems of a stochastic dynamic programming (SDP) based annual scheduling model aimed to calculate the water value of a hydropower plant is a fruitful effort. To this purpose, four 1000-year long simulations using the water value obtained from four different optimisation SDP-based scheduling models (three using mixed integer linear programming to solve the intrastage decision problems and other using linear programming) are compared. The results suggest that the small increase in profit does not make up for the necessary increase in computational time. Nonetheless, the study should be replicated using other hydropower plants and more complicated topologies in order to get more sound conclusions.
Ignacio Guisández, Juan Ignacio Pérez-Díaz

Coordinated Hydropower Bidding in the Day-Ahead and Balancing Market

Power producers with flexible production systems such as hydropower may sell their output in the day–ahead and balancing power markets. We present how the coordination of trades across multiple markets may be described as a stochastic program. Focus is on how the information structure inherent in the multi–market setting is represented through the scenario tree and mathematical modelling. In the model, each market is represented by a price or premium and an upper limit on the volume that can be traded at the given price. We illustrate our modelling by comparing coordinated versus sequential bidding strategies.
Ellen Krohn Aasgård

Assessing the Impacts of Integrating Snowpack Error Distribution in the Management of a Hydropower Reservoir Using Bayesian Stochastic Dynamic Programming (BSDP)

A hydropower system is presented in which long-term hydrological forecasts must be performed. The system is strongly snowmelt-dominated and the duration of the spring flood can last upwards of 5 months. The risk of flooding is very high when the snowpack is above long-term average values. This work analyzes the impacts of estimating and integrating the snowpack error distribution in a hydrological forecasting framework when optimized by a Bayesian Stochastic Dynamic Programming (BSDP) reservoir management optimization algorithm. The methodology follows two main steps. In the first step, the hydrological model is run on the historical dataset. The resulting hydrograph and hydrologic states are then compared to those of a synthetic “perfect” model simulation. An error distribution is defined between both series that can be used in the BSDP framework. Second, the first step is repeated with a classical SDP approach instead of BSDP to quantify the impacts of using the error distribution on hydropower generation. Results show that BSDP outperforms the classical SDP and that the snowpack error estimation plays a significant role in improving the reservoir management policy.
Richard Arsenault, Pascal Côté, Marco Latraverse

Inflow Forecasting for Hydropower Operations: Bayesian Model Averaging for Postprocessing Hydrological Ensembles

This paper contributes to forecasting of renewable infeed for use in dispatch scheduling and power systems analysis. Ensemble predictions are commonly used to assess the uncertainty of a future weather event, but they often are biased and have too small variance. Reliable forecasts for future inflow are important for hydropower operation, and the main purpose of this work is to develop methods to generate better calibrated and sharper probabilistic forecasts for inflow. We propose to extend Bayesian model averaging with a varying coefficient regression model to better respect changing weather patterns. We report on results from a case study from a catchment upstream of a Norwegian power plant during the period from 24 June 2014 to 22 June 2015.
Andreas Kleiven, Ingelin Steinsland

Benchmarking Hydro Operation by Use of a Simulator

The paper describes how a simulator is used to benchmark TrønderEnergis’ historical operation of one of their hydro systems. The simulator is a data program that simulates daily hydro optimization and scheduling tasks for the historical period 2005 to 2015. The purpose of the benchmark is to evaluate how good the historical operation has been and to point to which tasks in the decision process that is most important to improve (e.g. price forecasting, inflow forecasting or snow storage information).
Birger Mo, Sara Martino, Christian Naversen, Gunnar Aronsen, Ole Rismark

Optimal Pricing of Production Changes in Cascaded River Systems with Limited Storage

Optimization of hydroelectric power production is often executed for river systems consisting of several powerplants and reservoirs located in the same region. For hydropower stations located along the same river, the release from upstream reservoirs ends up as inflows to downstream stations. Calculating marginal cost for a string of powerplants with limited reservoir capacity between them, requires a new approach compared to heuristically calculating marginal cost for single plants in well-regulated hydrological systems. A new method, using marginal cost curves for individual powerplants to generate an overall marginal cost curve for interlinked power stations has been developed. Results based on a real-world case study demonstrate the advantage of the proposed method in terms of solution quality, in addition to significant insight into how optimal load distribution should be executed in daily operations.
Hans Ole Riddervold, Hans Ivar Skjelbred, Jiehong Kong, Ole Løseth Elvetun, Magnus Korpås

Modelling Tunnel Network Flow and Minimum Pressure Height in Short-Term Hydropower Scheduling

The paper proposes a method for modelling tunnel network flow between reservoirs and creeks above hydro power plants in short term hydro optimization. A method for handling pressure constraints in nodes in the tunnel network is also included. The method is applied on a plant below a reservoir and a creek, with a rigorous minimum pressure constraint in a tunnel. A comparison of the presented method with a manual adjustment method for handling the minimum pressure constraint shows a 3.3% increase in objective value of the original total sale.
Per Aaslid, Hans Ivar Skjelbred, Sigri Scott Bale

Implied Efficiency Curves from Analysis of Operational Patterns

A reservoir manager at a hydropower plant has to decide whether to release water in order to produce electricity, and the level at which to produce. These production levels have different efficiencies as well as other related technical aspects. Often, the plant will produce at the best efficiency point, i.e. release water at a rate that produces the highest amount of electricity per unit of water. We apply a structural estimation approach to a hydropower plant in the Norwegian electricity price zone NO5, in order to discover the managers’ preferences related to the different production levels. We use time series models in order to replicate the managers’ expectations of future conditions. The results show a greater willingness of the manager to produce at levels below than above the best efficiency point, which we argue is mainly due to the increased level of cavitation. They also imply that the reservoir managers’ preferences have changed over time, showing an increased willingness to produce at production levels both above and below the most efficient level.
Sebastian Brelin, Morten A. Lien, Stein-Erik Fleten, Jussi Keppo, Alois Pichler

Norway as a Battery for the Future European Power System – Comparison of Two Different Methodological Approaches

This paper compares the simulation results for two stochastic optimization power market models. EMPS uses aggregation and heuristics to calculate the optimal dispatch. SOVN simulates the operation of the power system in one large linear programming problem taking each single plant and reservoir into consideration. The comparison is for a future system in Europe where wind and solar power production supplies 61% of the annual demand. Three different alternatives for the Norwegian hydropower system is studied: present generation capacity (about 30 GW), increased capacity to about 41 GW and further to about 49 GW. The analyses show that SOVN to a larger degree than EMPS manage to increase production in high price periods and pump in low price periods. This particularly applies to the weeks before the change from the depletion (winter) to the filling (summer) period. This better ability to exploit the flexibility of the hydropower system is due to applying a formal optimization in SOVN compared to advanced heuristics in EMPS. For regions without pumping possibility, there is less difference between the models.
Ingeborg Graabak, Stefan Jaehnert, Magnus Korpås, Birger Mo

Backmatter

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